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We investigated the millennial variability (1000 A.D.-2000 A.D.) of global biogenic volatile organic compound (BVOC) emissions by using two independent numerical models: The Model of Emissions of Gases and Aerosols from Nature (MEGAN), for isoprene, monoterpene, and sesquiterpene, and Lund-Potsdam-Jena-General Ecosystem Simulator (LPJ-GUESS), for isoprene and monoterpenes. We found the millennial trends of global isoprene emissions to be mostly affected by land cover and atmospheric carbon dioxide changes, whereas monoterpene and sesquiterpene emission trends were dominated by temperature change. Isoprene emissions declined substantially in regions with large and rapid land cover change. In addition, isoprene emission sensitivity to drought proved to have significant short-term global effects. By the end of the past millennium MEGAN isoprene emissions were 634 TgC yr-1 (13% and 19% less than during 1750-1850 and 1000-1200, respectively), and LPJ-GUESS emissions were 323 TgC yr-1(15% and 20% less than during 1750-1850 and 1000-1200, respectively). Monoterpene emissions were 89 TgC yr-1(10% and 6% higher than during 1750-1850 and 1000-1200, respectively) in MEGAN, and 24 TgC yr-1 (2% higher and 5% less than during 1750-1850 and 1000-1200, respectively) in LPJ-GUESS. MEGAN sesquiterpene emissions were 36 TgC yr-1(10% and 4% higher than during 1750-1850 and 1000-1200, respectively). Although both models capture similar emission trends, the magnitude of the emissions are different. This highlights the importance of building better constraints on VOC emissions from terrestrial vegetation.

The Arctic region is warming considerably faster than the rest of the globe(1), with important consequences for the ecosystems(2) and human exploration of the region(3). However, the reasons behind this Arctic amplification are not entirely clear(4). As a result of measures to enhance air quality, anthropogenic emissions of particulate matter and its precursors have drastically decreased in parts of the Northern Hemisphere over the past three decades(5). Here we present simulations with an Earth system model with comprehensive aerosol physics and chemistry that show that the sulfate aerosol reductions in Europe since 1980 can potentially explain a significant fraction of Arctic warming over that period. Specifically, the Arctic region receives an additional 0.3Wm(-2) of energy, and warms by 0.5 degrees C on annual average in simulations with declining European sulfur emissions in line with historical observations, compared with a model simulation with fixed European emissions at 1980 levels. Arctic warming is amplified mainly in fall and winter, but the warming is initiated in summer by an increase in incoming solar radiation as well as an enhanced poleward oceanic and atmospheric heat transport. The simulated summertime energy surplus reduces sea-ice cover, which leads to a transfer of heat from the Arctic Ocean to the atmosphere. We conclude that air quality regulations in the Northern Hemisphere, the ocean and atmospheric circulation, and Arctic climate are inherently linked.

As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the micro biome. The bee micro biome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee micro biome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.

The TiN/SiNx nanocomposite and nanolaminate systems are the archetype for super if not ultrahard materials. Yet, the nature of the SiNx tissue phase is debated. Here, we show by atomically resolved electron microscopy methods that SiNx is epitaxially stabilized in a NaCl structure on the adjacent TiN(001) surfaces. Additionally, electron energy loss spectroscopy, supported by first-principles density functional theory calculations infer that SiNx hosts Si vacancies.

Single-column models (SCMs) have been used as tools to help develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing, which allows the testing of physical parameterisations in a controlled environment with reduced computational cost. Typically, either the ocean, sea ice or atmosphere is fully modelled and assumptions have to be made regarding the boundary conditions from other subsystems, adding a potential source of error. Here, we present a fully coupled atmosphere-ocean SCM (AOSCM), which is based on the global climate model EC-Earth3. The initial configuration of the AOSCM consists of the Nucleus for European Modelling of the Ocean (NEMO3.6) (ocean), the Louvain-la-Neuve Sea Ice Model (LIM3) (sea ice), the Open Integrated Forecasting System (OpenIFS) cycle 40r1 (atmosphere), and OASIS3-MCT (coupler). Results from the AOSCM are presented at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations, in situ observations are available for comparison. We find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution based on comparisons with buoy data, soundings and ship-based observations. The model evolution is sensitive to the initial conditions and forcing data imposed on the column. Comparing coupled and uncoupled configurations of the model can help disentangle model feedbacks. We demonstrate that the AOSCM in the current set-up is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions between the individual components of the system (atmosphere, sea ice and ocean).

We have studied a wide range of transition metals to find potential carbon nanotube (CNT) catalysts for chemical vapor deposition (CVD) production. The adhesion strengths between a CNT and a metal cluster were calculated using first principle density functional theory (DFT) for all 1st, 2nd and 3rd row transition metals. We have developed the criterion that the metal-carbon adhesion strength per bond must fulfill a Goldilocks principle for catalyzing CNT growth and used it to identify, besides the well known catalysts Fe, Co and Ni, a number of other potential catalysts, namely Y, Zr, Rh, Pd, La, Ce and Pt. Our results are consistent with previous experiments performed either in a carbon arc discharge environment or by a CVD-process with regard to CNT catalyst activity.

EDGE is a complex application for computational fluid dynamics used e.g. for aerodynamic simulations in avionics industry. In this work we present the portable, high-level parallelization of EDGE for execution on multicore CPU and GPU based systems by using the multi-backend skeleton programming library SkePU. We first expose the challenges of applying portable high-level parallelization to a complex scientific application for a heterogeneous (GPU-based) system using (SkePU) skeletons and discuss the encountered flexibility problems that usually do not show up in skeleton toy programs. We then identify and implement necessary improvements in SkePU to become applicable for applications containing computations on complex data structures and with irregular data access. In particular, we improve the MapArray skeleton and provide a new MultiVector container for operand data that can be used with unstructured grid data structures. Although there is no SkePU skeleton specifically dedicated to handling computations on unstructured grids and its data structures, we still obtain portable speedup of EDGE with both multicore CPU and GPU execution by using the improved MapArray skeleton of SkePU.

We study the effects of Rhenium (Re) deposited on epitaxial monolayer graphene grown on SiC(0001) and after subsequent annealing at different temperatures, by performing high resolution photoelectron spectroscopy (PES) and angle resolved photoelectron spectroscopy (ARPES). The graphene-Re system is found to be thermally stable. While no intercalation or chemical reaction of the Re is detected after deposition and subsequent annealing up to 1200 degrees C, a gradual decrease in the binding energy of the Re 4f doublet is observed. We propose that a larger mobility of the Re atoms with increasing annealing temperature and hopping of Re atoms between different defective sites on the graphene sample could induce this decrease of Re 4f binding energy. This is corroborated by first principles density functional theory (DFT) calculations of the Re core-level binding energy shift. No change in the doping or splitting of the initial monolayer graphene electronic band structure is observed after Re deposition and annealing up to 1200 degrees C, only a broadening of the bands. (C) 2017 Elsevier B.V. All rights reserved.